The Dawn of Abundance: Innovation Beyond Politics

By Garvin Jabusch.

The dream of abundance has haunted human imagination since Hesiod wrote of the Golden Age. From Francis Bacon’s “New Atlantis” to John Maynard Keynes’s vision of a fifteen-hour workweek, our greatest thinkers have glimpsed possibilities of transcending scarcity’s iron grip on human affairs. Yet never before has this ancient aspiration been so close to realization. Today, we find ourselves at an extraordinary inflection point in human history, where the convergence of breakthrough technologies, sustainable innovation, and evolving global production systems creates not just incremental change, but a phase transition in human capabilities that is fundamentally reshaping what’s possible.

This transformation offers an unprecedented possibility: a post-scarcity world operating within planetary boundaries. Far from utopian thinking—that perennial temptation of social philosophers—this prospect emerges as the realistic, logical conclusion of accelerating technological learning rates and economic evolution. Like the transition from agrarian to industrial society, except orders of magnitude faster, we stand before a transformation whose scope challenges our ability to imagine, even while its initial patterns are already present.

The Phase Change

To appreciate the magnitude of our current transformation, we must understand it through the lens of complex systems theory. Three concurrent revolutions—artificial intelligence, the energy transition, and advanced manufacturing (biotech too, but let’s hold that aside for a minute)—are not merely developing in parallel but creating unprecedented emergent properties through their interactions. This generates exponential rather than linear change, explaining why traditional political and economic frameworks, predicated on gradual, predictable evolution, combined with the assumption that the next 10 years will look a lot like the last 10, increasingly fail to capture reality.

This failure of traditional institutions to grasp or respond to the pace of change recalls Thomas Kuhn’s analysis of paradigm shifts in scientific revolutions. We’re experiencing not just technological advancement but a fundamental shift in how human economics operates, one that renders many historical assumptions about scarcity, value creation, and economic organization obsolete. The old ways of governing, regulating, and managing economic systems prove increasingly inadequate for a world where technological learning rates reshape the very foundations of production and consumption.

The Power of Learning Rates

At the heart of this transformation lies a phenomenon that economists have long understood but whose implications we are only now beginning to fully grasp: technological learning rates. These rates—the speed at which we improve at building and implementing new technologies—create what complexity theorists would recognize as a positive feedback loop of unprecedented scale and scope. As Brian Arthur demonstrated in his work on increasing returns, such feedback loops can fundamentally reshape economic landscapes.

Consider the profound implications of recent empirical evidence: MIT researchers discovered that AI-enabled materials chemists achieved 44% more novel material discoveries and generated 18% more downstream innovation than traditional methods. This represents not merely an improvement in efficiency but a meta-level acceleration in our capacity for discovery itself—a second-order change that transforms the very process of innovation. According to current research, AI is significantly accelerating drug discovery too, potentially reducing the timeline for identifying drug candidates from years to months, with some estimates suggesting a 15-fold speedup in the process, drastically improving efficiency and lowering costs by up to 70% in some cases; and AI-discovered drugs exhibit greater success in early clinical trials than those discovered using traditional techniques, as “Phase 1 trials for AI-discovered drugs have shown success rates between 80-90%, significantly higher than the historical industry averages of 40-65%”.

These accelerations manifest through what economists call a flywheel effect: as technology improves, costs decrease, markets expand, investment increases, and scale effects accelerate improvement. Each cycle moves faster than the last, creating exponential progress that defies linear extrapolation from historical experience. We see here not just the continuation of something like Moore’s Law, but its expansion into domains far beyond semiconductor manufacturing.

This is not only accelerating productivity, efficiency and wealth creation, but also reducing planetary risks. According to Green Alpha’s first pillar of Next EconomicsTM, which we based on E.O. Wilson’s pioneering work on island biogeography, “to provide universally reasonable standards of living, without crossing planetary boundaries and therefore risking large-scale disruptions, the global economy must continually and dramatically improve its productive capacity.”

The Zero-Marginal Cost Revolution

Silicon Valley’s evolution from semiconductors to software provides not just a historical example but an essential template for understanding how post-scarcity becomes possible. The economic model pioneered there—massive upfront investments yielding minimal marginal costs and theoretically unlimited returns at scale—now extends far beyond the digital realm into the physical world.

This extension represents what Jeremy Rifkin termed “the zero marginal cost society,” but with a crucial difference: we now possess the technological means to actually achieve it. Artificial intelligence dramatically reduces the cognitive costs of knowledge work while simultaneously accelerating innovation across sectors. Advanced manufacturing, powered by robotics and AI, pushes toward zero-marginal cost production in physical goods. Renewable energy systems, with their significant-but-ever-cheaper upfront costs and minimal operating expenses, create the foundation for energy abundance that undergirds this entire transformation.

The implications of this shift are massive: When the marginal cost of production approaches zero across multiple domains simultaneously, the very nature of economic activity transforms. We move from an economy of scarcity management to one of abundance creation.

The Self-Reinforcing Nature of Progress

What distinguishes our current moment is the unprecedented interaction between these systems, creating what complexity theorists call emergent properties. When AI accelerates renewable energy development, it leads to cheaper energy, which enables more computing power for AI development. This improved AI then enhances manufacturing efficiency, which reduces the cost of producing renewable energy infrastructure. Each revolution of this cycle happens faster than the last, creating an acceleration that compounds upon itself.

Consider the case of Galvorn, a carbon-negative steel replacement. While currently more expensive than traditional steel, technological learning rates promise to drive costs down predictably and inevitably. This pattern, already demonstrated in solar panels and batteries, represents not an isolated example but a blueprint for how post-scarcity becomes possible across multiple domains. The experience curve, first identified by Bruce Henderson at Boston Consulting Group, operates here with unprecedented force and scope.

The New Global Division of Labor

The current global economic structure, rather than hindering this transition, accelerates it through what organizational theorists would recognize as specialized optimization at a planetary scale. Innovation hubs focus on design work with zero marginal costs, while technical centers handle manufacturing with minimal marginal costs. Component production distributes globally, and final assembly follows efficiency patterns. This creates not just a supply chain but a global learning system that maximizes the rate of improvement while minimizing costs.

This distributed system proves particularly powerful because it allows different regions to specialize in their areas of comparative advantage while contributing to the overall acceleration of progress. Here, Ricardo’s principle of comparative advantage operates not just at the level of goods but of innovation itself, creating what Michael Porter would recognize as a new form of competitive advantage based on learning and capability development.

The resulting global innovation network exhibits characteristics of what complexity theorists call a scale-free network, where hubs of specialized expertise connect through dense webs of knowledge exchange and production relationships. This structure proves remarkably resilient to disruption while maximizing the speed of technological advancement and knowledge diffusion.

Beyond Traditional Manufacturing

The transformation of traditional industries illustrates this new paradigm with particular clarity. Consider the evolution of the automobile industry: electric vehicles represent not merely a change in propulsion technology but a fundamental reimagining of transportation as a software-defined, modular platform. The physical vehicle becomes a substrate for continuous improvement through software updates, while production increasingly approaches the zero-marginal cost ideal through automation and AI-driven optimization. Understanding this has made Tesla and several Chinese EV makers extremely price competitive with their sophisticated EVs, while automakers slower to embrace innovation continue to sell every EV they make at significant negative margins, even while offering inferior products at less competitive prices.

This pattern repeats across industries as products become more modular, software-defined, and automated in their production. The key insight is that we’re not simply making traditional goods more efficiently—we’re fundamentally redefining what production and consumption mean in a world of abundant energy and intelligence. You might be thinking his transformation recalls Schumpeter’s concept of creative destruction, and you’re right, but it is now operating at an unprecedented scale and speed.

The Three Pillars of Post-Scarcity Production

The transition to post-scarcity rests upon a tripartite foundation that echoes the industrial revolution’s transformation of human productive capacity, yet operates at a fundamentally different level of speed, complexity and capability:

  1. The Zero-Marginal Cost Core. This foundation represents the culmination of digitalization’s promise: AI-driven design and optimization, software-defined functionality, renewable energy systems, and automated production converge to create productive capacity that approaches true zero-marginal cost at scale. Unlike previous productive revolutions, this core generates not just efficiency but fundamental abundance. Sometimes this is less formally equated with dematerialization of an economy.
  2. Distributed Manufacturing Networks. These networks transcend traditional concepts of the supply chain, creating instead what might be termed “responsive production webs.” Through modular production platforms, localized final assembly, AI-optimized supply chains, and automated quality control, they achieve both unprecedented efficiency and adaptability. Being broadly and often locally distributed, they are also more resilient and disruption resistant.
  3. Global Innovation Networks. Perhaps most crucially, these networks leverage specialized regional capabilities and cross-border knowledge flows to create what Michael Polanyi would recognize as a new form of distributed knowledge creation, one that maximizes both tacit and explicit knowledge development.

The Technology Convergence Accelerator

The convergence of multiple technologies creates what systems theorists would term a positive feedback loop of unprecedented scale. Artificial intelligence serves as a meta-technology, accelerating progress across all domains while improving itself in the process.

Renewable energy systems transform our relationship with power generation and consumption in ways that would have astonished the theoretical pioneers of thermodynamics. Instead of managing scarcity through complex extraction and distribution networks (oil wells and supertankers), we’re moving toward systems of energy abundance based on capturing virtually limitless solar and wind resources, close to where the energy will be used. This abundance, in turn, enables other transformative technologies.

Advanced materials science and biotechnology are reimagining the very building blocks of our physical world. By creating new materials with precisely engineered properties and developing biological systems that can produce complex molecules efficiently, we’re breaking down traditional resource constraints. This represents what the Santa Fe Institute would recognize as a new level of complexity in our manipulation of matter and energy.

The Investment Imperative

The capital allocation required for this transformation differs fundamentally from traditional industrial development. Rather than simply scaling existing systems, we’re building new infrastructures that become more efficient and capable over time through learning effects. This includes not just physical infrastructure but also the digital systems and human capital necessary to operate and improve these systems.

This investment pattern involves tighter feedback loops where the accelerations are more pronounced. The investment in core technologies—AI, energy systems, advanced manufacturing, and biotechnology—creates platforms that enable further innovation at an accelerating pace. If our goal is a post-scarcity economy that thrives within the planetary boundaries, we must accelerate investments in these areas (and slow them in areas that accelerate risks like climate change, but that’s another post).

Addressing the Challenges

While the challenges ahead are significant, technological learning rates suggest they are fundamentally surmountable. Political resistance and incumbent industries may slow adoption in certain regions, but they cannot stop the global progress of technologies that offer clear economic advantages. Whale oil merchants and horse breeders were ultimately powerless to stop the spread of earlier general-purpose technologies like electricity or the internal combustion engine.

The economic transition, while at some level disruptive, opens new possibilities for human flourishing. As AI and automation handle routine tasks, human creativity and innovation become more valuable. The challenge isn’t preventing job displacement but ensuring that the benefits of abundance are widely shared and that humans are prepared for the new opportunities that emerge.

The Path Forward

The transition to post-scarcity requires coordinated action across multiple domains, but this coordination emerges more from aligned incentives than central planning (think: zero marginal cost solar energy, as opposed to diplomats hobnobbing at COP29), and therefore has a realistic shot at success. As technologies improve and costs decline, market forces naturally drive adoption and innovation. Policy frameworks can accelerate or delay this transition but cannot fundamentally alter its direction.

Investment patterns increasingly recognize this reality, with capital flowing toward transformative technologies that promise to reshape entire industries. The development of these technologies creates new possibilities for human development and environmental restoration, forming a virtuous cycle of improvement that recalls the optimistic visions of the Enlightenment, but with the technological means to actually achieve them.

And the pace of innovation is now as slow as it will be again within the lifetime of anyone trading this, and probably much longer. While speculative, I believe the Law of Accelerating Returns, already playing out, will prove to have been roughly accurate.

Another way to think about knowledge accumulation is in its totality. In 1982, American systems theorist Buckminster Fuller introduced the concept of the Knowledge Doubling Curve, wherein he observed that:  

  • Until 1900: Human knowledge doubled approximately every century.
  • By 1945: Knowledge was doubling every 25 years.
  • By 1982: Knowledge was doubling every 12-13 months.  

Obviously, knowledge and the innovation and technology to create more knowledge, have come a long way since 1982, and in 2020 IBM estimated the totality of human knowledge was doubling about twice per day. This is obviously far faster than an individual human can assimilate information, which is why it is as important as it is concomitant (and in a causal pathway) that we have increasingly powerful AI tools with which to manage knowledge and information. It is worth remembering as well that IBM hasn’t updated their estimate since 2020.

Conclusion: The Inevitable Transition

We stand at the beginning of a phase change in human history, one that promises to transform scarcity into abundance through the convergence of accelerating technologies, learning rates, and global networks. While challenges exist, the self-reinforcing nature of technological progress makes this transition increasingly inevitable.

The key to understanding this transformation lies in recognizing that we’re not simply improving existing systems but creating entirely new paradigms for human organization and production. Learning rates drive exponential improvement, technologies converge to accelerate progress, and global, regional, and local networks maximize innovation speed. Political resistance may create temporary barriers, but it cannot stop the fundamental evolution of human capability. We are observing massive structural trends that are not reducible to shifting political climates.

The future belongs not to those who trade in or try to preserve scarcity, but to those who understand how to harness and accelerate these trends toward abundance. The technologies exist, the economic models are emerging, and the path forward becomes clearer each day. We are not just postulating the possibility of post-scarcity—we are witnessing its birth.

This moment recalls Keynes’s optimistic vision of abundance, but with a crucial difference: we now possess the technological means to actually achieve it. The question before us isn’t whether this transformation will occur, but how we choose to shape and direct it, and if we can actualize it in its fullness in time to avoid the consequences of planetary, systemic risk. By understanding and embracing these changes, we can work to ensure that the coming abundance benefits all of humanity while respecting planetary boundaries.

The dawn of abundance is here, and with it comes the opportunity to create a world of unprecedented possibility for everybody. This is not only an aspiration but also an emerging reality, driven by the inexorable logic of technological progress and human ingenuity. Our task now is not to question whether this transformation is possible, but to ensure it unfolds in ways that enhance human flourishing and planetary stability.

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